How the Cloud Has Evolved Over the Past 10 Years

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Read more about author Gilad David Maayan.

Over the years, cloud computing has turned from an innovative concept into a disruptive endeavor. Today, cloud computing is a booming industry in which organizations and researchers continue to push the boundaries of what is possible and provide new and improved solutions for critical problems.

This article briefly examines some of the most important events in the history of cloud computing and calls out four of the most important cloud trends developing today.

A Brief History of Cloud Computing

Although many think of cloud computing as a relatively recent concept, in some ways it can be traced back as far as the mid-1940s. Subsequent to Alan Turing’s 1930s work on early computing and the ultimately unprovable Entscheidungsproblem (the notion that a statement is universally provable with enough computing power), early general-purpose, Turing-complete mainframes, like the ENIAC, were introduced. This type of computing involved massive, shared, and expensive machines capable of performing computations mechanically, by manipulating components like vacuum tubes and relays.

In those days, while not all programmers needed constant access to the machine, as they do today, many different people and teams would program and run the mainframe. To ensure that users had access when they needed it, “time-sharing” schedules were created.

These schedules would evolve to enable users to access the mainframe from any connected stations or “dumb terminals” and use the computing power of the mainframe from a tethered screen. While this is very different from modern cloud computing, the basic premise is the same.

cloud computing
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A few decades later, the field of cloud computing advanced again when J.C.R. Licklider, a computer scientist, proposed an interconnected system of computers. In 1969, this concept was developed into the Advanced Research Projects Agency Network (ARPANET), a primitive version of the internet.

ARPANET was the first network that enabled digital data to be shared between remote computers. The idea behind ARPANET and Licklider’s vision was to create a system where everyone in the world could be interconnected and information was universally accessible.

Many advancements came in the following decades, including the release of IBM’s Virtual Machine (VM) operating system in 1972. This OS enabled the creation of a virtual computer that operated just like a physical one. Along the way, similar consumer-grade technologies would appear: Parallels for Mac was a popular hardware virtualization platform and many Linux users today rely on tools like Vagrant for the same functionality.

Eventually, this was turned into the creation of “virtual” private networks used by businesses. Then, in the 1990s, modern cloud computing infrastructure was developed. Salesforce became the first company to offer a software-as-a-service (SaaS) over the internet – made possible by cloud computing.

By 2006, Amazon Web Services (AWS) was created and the Elastic Compute Cloud (EC2) service was released. This service enables customers to rent virtual machines as infrastructure for their data and applications. This was the same year that Google released Google Docs, a now well-known cloud service used to create, edit, and share documents in the cloud.

Then, in 2007, Google, IBM, and several universities worked together to create a server farm with resources dedicated to research projects in the cloud. That same year, companies like Netflix began launching streaming services.

Around the same time, technologies supporting massive amounts of data began to appear, starting with the 2004 MapReduce paper from Google. With the introduction of Hadoop a few years later, it became possible to manage extremely large datasets on commodity hardware.

Apache Cassandra made it possible to distribute data across hundreds or even thousands of nodes while managing read- and write- queries in a dialect very similar to standard SQL. This capacity to store and distribute massive amounts of data – and the possibilities for collecting, transporting, storing, and using data – made cloud storage and management even more compelling.

Cloud Computing Over the Past 10 Years

While initial growth may have been slow, in the last 10 years, cloud services have expanded significantly. By 2010, Amazon, Google, Microsoft, and OpenStack had all launched cloud divisions. This helped to make cloud services available to the masses. Since then, these services have taken over a large part of the tech industry and cloud transitions or migrations have become common.

As cloud services were adopted by organizations, eventually the idea of using public and private clouds together was born. These “hybrid clouds” enabled organizations to better customize their implementations and integrate cloud services more fully. In 2011, iCloud was released by Apple, enabling consumers to begin using cloud storage in their daily lives.

In the past 10 years, businesses of all sizes have adopted cloud services readily in pursuit of improved services and long-term cost savings. According to Gartner, over a third of organizations consider cloud computing as one of their top three investment priorities.

Due to this adoption, software-as-a-service (SaaS) offerings used by organizations doubled between 2015 and 2017. Additionally, many startups joined the market. In India alone, 55 new SaaS companies were founded in 2017.

However, infrastructure-as-a-service (IaaS) has been the largest area of growth. In 2018, the IaaS market was dominated by five providers: Google, Amazon, Microsoft, Alibaba, and IBM. Industry values reflect this – starting at around $12 billion in 2010, revenues are predicted to exceed $623 billion by 2025.

Foundational Cloud Computing Trends

In addition to the growth of services as a whole, there have also been several trends that have shaped cloud computing. Some of the most important of these trends are explained below.

1. Containers

Containers are packaged applications, operating systems, and/or data that can be operated flexibly across environments. This is because dependencies and binaries are packaged with applications, abstracting operations from the host operating system.

The use of containers has been essential to the expansion of cloud services and are the base on which cloud-native applications are built. According to Forrester, one in three organizations are using or are planning to use containers in their production environments.

Containers are popular largely because this technology helps businesses ensure portability across cloud services. This in turn supports DevOps strategies and allows for more productive teams and products.

2. Serverless Computing

Serverless computing is computing performed on managed infrastructure. It removes the responsibility for back-ends from IT and DevOps teams and enables engineers to focus solely on application or code functionality. Examples of serverless services include AWS Step Functions, Azure Functions, and Google Cloud Functions.

Serverless computing also enables businesses of all sizes to access resources with no upfront costs or hardware purchases required. This makes it appealing since businesses can more easily experiment with resources and code before making large investments.

3. Cloud Security

As cloud services have gained in popularity, the risks for data and applications hosted in the cloud have grown as well. This has driven the growth of cloud-based security and data privacy.

Cloud security has contributed to the growth of cloud services in several ways. Major cloud providers have included enterprise-grade security features into their services. Cloud-based security solutions have also been developed to secure data in the cloud as well as on-premises.

Additionally, managed cloud security services have been gaining popularity. These are third-party services that manage the security of a business’s resources for them.

4. Edge Computing

The distributed nature of cloud resources has drastically changed the expectations of latency and accessibility. The sheer number of users and amount of data transferred between cloud services has had to continually expand. Edge computing has contributed to this expansion by moving data analytics and compute operations closer to users and devices.

With the growth of big data and the Internet of Things (IoT), edge computing is creating significant opportunities. This type of computing can facilitate real-time data analysis and enable improvements for the application of artificial intelligence. This can make cloud resources even more accessible and beneficial to organizations that were previously limited by latency constraints.

5. Managed Open-Source Services

Managed open-source service providers allow you to outsource the hosting responsibilities of your open-source deployments to public cloud hosting providers like AWS, GCP, Azure, and more.

In addition to outsourcing hosting, managed service providers automatically maintain your services – with features like automatic version updates, data replication, etc. The main value of a managed service is to allow you to focus on your data and applications, rather than the underlying infrastructure.

Managed services bring reliability and stability to your open-source deployments, and allow you to build performant data pipelines in minutes, with little to no maintenance worries.

6. High-Performance Computing (HPC)

In the past, very large computations or data processing jobs required supercomputers, which were possessed only by very large organizations, universities, or governments. With the advent of the cloud, supercomputer infrastructure is becoming available to any organization.

All major cloud providers offer HPC instances, which are highly parallelized and offer huge computing capacity at affordable cost. Organizations are using these HPC cloud resources for compute-intensive workloads like genomics, risk management, and big data analysis.

In Summary

Cloud computing is not new, and the technology continues to evolve. At first, during the 1940s and 1950s, thinkers and innovators developed cloud concepts – ideas, software, and hardware – to address some of the problems proposed and examined prior.

Eventually, during the 1990s, cloud computing infrastructure as we know it today was developed. In the early 2000s, AWS was founded and released the then-new EC2 service. Subsequently, “big data” technologies emerged to support edge computing, among other things.

Over the past 10 years, many more companies, such as Microsoft Azure and Google Cloud Platform, joined the cloud landscape to offer unique cloud services. Today, cloud computing is not only a field, it is also a development mindset. This shift creates more disruptions in its wake, advancing relatively new fields such as cloud-native development, edge computing, and serverless infrastructure.

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